Evolution Of Industrial Structure Research Articles

The Relationship Between a Green, Low-carbon and Recycling Economy, Economic Policy and Industrial Structure Development

This article critically examines Charles Bonnet’s seminal contributions to experimental science, particularly through his influential work, ‘Research on the Use of Leaves.’ The primary objective is to delineate the functions and forms of natural experimentation as they were understood and practiced in the mid-18th century. During this period, scientists esteemed experimentation as the zenith of scientific proof, acutely cognizant of its multifaceted functional and typological aspects. Their methodology was characterized by a detailed narration of research methodologies, fostering a ‘rhetoric of transparency’ in scientific discourse. Nevertheless, the advent of new norms in scientific discourse during the 19th century, coupled with a paradigmatic philosophical shift in the 20th century, resulted in the marginalization of empirical practices of the Enlightenment era. Contemporary historians are now endeavoring to reconcile significant terminological discrepancies and to recontextualize the divergent methodologies among natural historians of that epoch. This involves a critical distinction between exploratory and demonstrative (or discriminant) forms of experimentation. Bonnet’s systematic preference for discriminant experimentation serves as a quintessential example of the logical approach in natural history. However, this perspective does not wholly represent the 18th-century ‘art of observation,’ which embraced a plethora of methodologies including taxonomy, anatomical dissection, chemical analysis, and physical measurements.

Can industrial structure optimization and industrial structure transition both lead to carbon lock-in mitigation? The case of China.

The optimization and transition of the industrial structure help improve the quality of the economy, moving it toward low-carbon development. By using the Instrumental Variable Generalized Method of Moments model and a city-level dataset covering the period 2006-2019, this paper explores the carbon lock-in mitigation effects of industrial structure optimization and industrial structure transition, respectively. The heterogeneity and the synthetic industrial structure adjustment effect are detected, and the potential impact mechanism is also explored. Some findings have been generated. (1) Both industrial structure optimization and industrial structure transition realize carbon lock-in eradication. (2) Industrial structure optimization and transition are more effective in inhibiting carbon lock-in in cities with a higher level of economic background. (3) By generating an interaction term of industrial structure optimization and transition and examining the impact of the interaction term on carbon lock-in, this paper detects that industrial structure optimization and transition have a synthetic impact on carbon lock-in, showing a "1 + 1 > 2" effect. (4) Industrial structure optimization and transition both affect carbon lock-in by improving technological innovation level, which is the impact mechanism. Some policy implications, such as sectoral diversification and promoting research and development, are put forward for better industrial structure development and carbon unlocking.

Technological innovation and its influence on energy risk management: Unpacking China’s energy consumption structure optimisation amidst climate change

In the context of intensifying climate challenges, adept energy risk management is more pertinent than ever. This research pioneers an in-depth exploration into China’s pronounced reliance on high-polluting fossil fuels, utilising a decade’s worth of provincial data (2010–2020) to shed light on the intricate dynamics between technological innovation and energy consumption structure refinement. Notably, our findings unveil that technological advancements act as catalysts in streamlining energy consumption structures, serving as a bulwark against emergent climate-related risks. Yet, this positive trajectory is not immune to disruptions: volatility in crude oil futures prices has the potential to dampen these benefits, ushering in heightened financial risks. Our work further underscores pronounced regional variances; technological innovation yields diminished returns in the central and western regions compared to their eastern counterparts. An intriguing observation is the resilience exhibited by coal-dependent provinces to technological evolution, pointing towards entrenched energy infrastructure challenges. Crucially, this study is among the first to identify the dual roles of industrial structure evolution and energy pricing dynamics as mediators in energy risk management. Drawing from these insights, we advocate for a proactive harnessing of technological innovation, not merely as a tool, but as an imperative to drive China’s energy transformation, foster sustainable consumption, and lay the foundation for a fortified green and low-carbon technological ecosystem.

Research on industrial structure adjustment and spillover effect in resource-based regions in the post-pandemic era.

Resource-based regions support national economic development and are essential sources of basic energy and raw materials. In the post-pandemic era, however, there are practical situations to deal with, such as a fractured industrial chain, a weaker industrial structure, and a sharp reduction in economic benefits. Based on data collected from 68 cities in China, from 2010 to 2021, with 816 observations, this paper explores the industrial development process of resource-based regions in China and the change in the toughness of the industrial structure under the impact of COVID-19. The paper studies and analyzes industrial development trends, industrial structure toughness, and spatial spillover effects. The methods used are the Markov chain model and the Industrial Structure Advancement Index. By building the spatial Dubin model, the paper analyzes the spatial spillover effect of regional industrial development. It decomposes the spillover effect using the partial differential model based on regression. The results show that, during the study period, the comprehensive development level of industries in resource-based regions in China was slowly improving and tended to stabilize after entering the post-pandemic era. The evolution of an advanced industrial structure is significantly heterogeneous among regions, and each region has different toughness. The impact of COVID-19 has reduced the toughness of China's resource-based regions' industrial structure. The spatial spillover effect of regional industrial development is significant. Labor force, technology input, and industrial-structure optimization have different impacts on the industrial development of neighboring regions. In the post-pandemic era, China has used new management methods for more innovation. In order to achieve low-carbon, environmental protection, and sustainable development of resources, realize the rapid recovery of the toughness of industrial structure in China's resource-based cities, and reduce the impact of the COVID-19 pandemic, China proposes to expand the supply of resources, improve the allocation of resources, optimize the direction, promote the rational flow and efficient aggregation of various factors, and enhance the impetus for innovation and development.

The potential nexus between fintech and energy consumption: A new perspective on natural resource consumption

In fintech innovation, conventional financial service limits are exceeded, contributing to regional sustainable development by reducing strain on resources. It is crucial in mitigating the demand for natural resources (e.g., fossil energy consumption), essential for achieving regional sustainability. To investigate this, we examine how fintech influenced fossil energy consumption in 272 cities between 2006 and 2019, using fixed and threshold regression models. The findings underscore that fintech exerts a significant influence in escalating fossil energy consumption and augmenting energy intensity. Notably, the impact of fintech on fossil energy consumption witnesses a distinct hierarchical pattern, with prevalence in the eastern regions surpassing that of the central and western counterparts, and the impact of fintech on energy intensity is more prominent in western China. Fintech stimulates fossil energy consumption in the high-level fintech group while exhibiting insignificance concerning energy intensity in the low-level fintech group. A heightened degree of marketization can moderate fintech's impact on energy consumption and curbing energy intensity. Notably, a threshold in fintech development emerges at 3.466, where lower levels inhibit energy consumption, while levels exceeding 3.466 demonstrate a stimulative effect on energy consumption. The industrial structure is moderating in the nexus between fintech and urban fossil energy consumption, showcasing a threshold value of 0.268. When the industrial structure's developmental level is below this threshold, fintech promotes fossil energy consumption. while levels exceed 0.268 in industrial structure development, fintech facilitates energy conservation by restructuring industries. These findings offer relevant policy recommendations. Our findings can help alleviate resource consumption pressure through fintech and further informing the green and low-carbon transition of cities.

Innovative Research on Industrial Upgrading and Transformation Path of Regional Economy in the Perspective of Digital Economy

Abstract This paper utilizes the digital economy, regional spatial distribution digital mining technology, establishes the indicator system, assigns values to the indicators, and applies the indicator system to evaluate the development of industrial structure upgrading and transformation of the regional economy. According to the research results of the basic structure and algorithm of the self-organized neural network model, combined with the classification layer smoothing algorithm, the regional spatial clustering model is constructed. Using the constructed model, the regional economic spatial dynamic data is mined, and the path of industrial transformation and upgrading in the regional spatial area is dynamically studied. Furthermore, using the CA algorithm, the evolution law of land use structure in the region is predicted, and the development of the regional economy is inferred. At the same time, through the spatial autocorrelation regional prediction model, the relevant regional spatial expansion prediction method is proposed, the three research hypotheses of this paper are made, and the constructed model is utilized to innovate the exploration of industrial transformation and upgrading paths from the spatial dimension. Using empirical research methods, descriptive statistics, and mediating effect heterogeneity analysis are carried out to analyze the factors that influence regional economic variables in place A. The empirical analysis shows that the fluctuation range interval of industrial structure is between [0.811,10.2805], which brings a large positive impact on the regional economy.2017 national digital economic growth rate changed from -0.17446 to 0.17143 to realize a positive growth rate, and at the same time, there is a heterogeneity in the development of the east-west and central regions of A. The hypotheses presented in this paper are all valid.

Research on the Role of Digital Economy in Industrial Structure Optimization Evidence from China's Provincial Panel

The development of digital economy not only promotes economic growth, but also promotes the optimization and development of industrial structure. Using the panel data of 31 provinces provided by China Statistical Yearbook, this paper constructs two indicators of digital economy and industrial structure optimization, and uses two-way fixed effect model to study the impact effect, heterogeneity analysis and mechanism analysis of digital economy on industrial structure optimization. The research shows that the development of digital economy has significantly optimized the industrial structure; In different regions of China, the role of digital economy in the optimization of industrial structure is different. The improvement of innovation level and social division of labor will significantly promote the optimization effect of digital economy on industrial structure. The results of this study show that it is necessary to further promote the integration of digital economy and the traditional three industries, and give full play to the enabling role of digital economy with higher quality. We should pay attention to the different impacts of digital economy on industrial structure optimization in different regions and take measures according to local conditions. It is necessary to refine the social division of labor in the region and strengthen the regional innovation ability, so as to give full play to the optimization efficiency of digital economy on industrial structure.

Research on the Development of Industrial Structure in Zhejiang Province from the Perspective of Planning

Research on the Development of Industrial Structure in Zhejiang Province from the Perspective of Planning

How can China’s coal cities achieve high-quality development?—An empirical study based on the “resource curse” hypothesis

The relationship between the utilization of natural resources and high-quality economic growth has always been a concern of the academic community. China’s coal cities to varying degrees suffer from population outflow, economic stagnation or even negative growth, precipitous drop in housing prices, serious environmental damage, and other problems. There is a negative correlation from the perspective of location between the enrichment of coal resources and economic development in China, confirming the existence of coal “resource curse” in China’s interprovincial scope. Through establishing quantitative models. This article analyzes the transmission mechanism of the nonlinear impact of coal industry development on regional total factor productivity (TFP) from the 2 paths of industrial structure evolution and factor allocation efficiency. The sample panel data of 44 coal cities in China from 2003 to 2017 are examined to empirically test the impact of coal industry development in China’s coal cities on TFP and its transmission mechanism. In the coal industry development, the service industry is being squeezed out to some degree, while the manufacturing industry is suffered from “double deindustrialization” and severe shrinkage. Such an industrial structure transformation is one of the transmission paths of “resource curse.” The development of human capital (HC) and finance has a threshold effect on the impact of the coal industry development on the TFP of coal cities. The excessive growth of coal industry has a restraining effect on the development level of HC and finance that influences the efficiency of resource allocation, resulting in failure of such industries to promote the TFP. With the improvement of HC and finance sectors in coal cities, the development of coal industry has promoted the TFP. Therefore, this article holds that the government should aim at improving the efficiency of factor allocation, formulate scientific and reasonable industrial adjustment policies, upgrade industrial structure, and actively develop manufacturing and producer services. Meanwhile, in the process of coal city development, it should pay attention to improving HC input, actively develop green finance industry to promote the development of capital market, and promote the green transformation of coal industry. Actively develop new sources of energy. The sustainable development of coal cities should be guided according to different life cycle stages in order to achieve healthy and sustainable development and break the “resource curse.”

Natural resources, financial development and structural transformation in Sub-Saharan Africa

Structural transformation is a crucial prerequisite for inclusive and sustainable development. In this context, this study examines the influence of natural resource dependence on the transformation of industrial structure in a panel of 30 Sub-Saharan (SSA) economies from 1995 to 2019, taking into account the role of financial development. The empirical analysis relies on the newly developed bias-corrected method-of-moments estimator. The findings indicate that natural resource dependence leads to a reduction in the output contribution of the manufacturing and service industries. On the other hand, financial development through the institutions channel decreases the output value of extractive industries while increasing the output value of manufacturing and service industries, resulting in a net positive effect on the evolution of industrial structure away from extractive-based industrialization. Considering the complex multidimensional nature of financial development, further findings suggest that the depth and efficiency of financial systems are critical areas for deepening structural diversification in the sub-region. Additionally, the findings reveal a U-shaped relationship between per capita GDP and industrial structure transformation. These findings highlight that natural resource dependence inhibits structural transformation in SSA and emphasize the importance of enhancing the depth and efficiency of financial systems as part of strategies to break the resource curse.

Perception Analysis of the Transformation from a Fishery-Led to Industry-Led Island with its Human Settlement Changes: A Case Study of Liuheng Island, Zhoushan City, China

Based on the theories of industrial structure and settlement environment, this paper conducts a quantitative and qualitative study to investigate how the evolution in the industrial structure of the island affects the settlement environment with relevant statistical data, local chronicles, and questionnaire survey data. The study found that the industrial structure of Liuheng Island has transformed from a fishery-led to industry-led island, which has led to the rapid increase of urbanization on Liuheng Island, and the public service facilities have been increasingly densely distributed urban-type communities with high modernization levels, such as Longshan Community, Xuanzhuotou Community, and Taimen Community. The local residents of Liuheng Island are also satisfied with the public service facilities in terms of facility availability, transportation convenience, environmental comfort, and environmental health. For a period, the island residents were particularly concerned about the regional differences in environmental health, and the main reasons were the industrial structure upgrade towards industrialization, which would cause certain industrial waste emissions, and the pressure of commuting within the island, which would affect residents’ sense of security. This indicates that the evolution of industrial structure will directly affect the speed and quality of urban and rural settlement hardware construction and also, to a certain extent, the subjective perceptions of residents around the dense industrial areas on the state of the settlement, especially in terms of environmental health and community living safety.

Research on the coordinated development of resource-based cities in Sichuan Province: from the perspective of industrial structure and ecological environment

During their journey of developing, resource-based cities gradually deplete the resources on which they rely for survival. Scientific and reasonable research on the industrial and ecological aspects of resource-based cities is conducive to the coordinated development of cities. In order to further analyze the industrial structure of resource-based cities systematically and analyze the comprehensive level of resource-based cities from multi-dimensional perspective. This paper took 8 resource-based cities in Sichuan Province as the research object, and constructed the index system from two systems: industrial structure and ecological environment, then the shift-share analysis, entropy weight method and capacity coupling coefficient model were used to analyze their level of industrial structure, ecological environment and the coupling relationship respectively. According to the results of the study, it can be concluded that the main influencing factor in the development of industrial structure is the industrialmix effect, while the ecological level presents a decreasing level due to the lack of control of total industrial solid waste and energy consumption. The coupling degree between industrial structure and ecological environment in resource-based cities in Sichuan Province is relatively stable, and the coupling coordination degree also gradually tends to a stable state. In the subsequent development, the focus should be on the coal mining and dressing industry and the power, heat production and supply industry. Starting with the actual industrial structure of resource-based cities and specific indicators that affected the ecological environment, this paper hereby analyzed the development momentum and unified and coordinated development status of resource-based cities. The main purpose of this paper is providing some technical support for resource-based cities to improve their coordinated urban development, and giving policy suggestions for the coordinated development of resource-based cities.

The Harmonious Relationship between Energy Utilization Efficiency and Industrial Structure Development under Carbon Emission Constraints: Measurement, Quantification, and Identification

Addressing the challenge of attaining a harmonious balance between energy utilization efficiency and the level of industrial structure development is crucial for promoting regional sustainable development. Aiming at the goal of carbon neutrality, a three-stage method to analyze the relationship between energy utilization and industrial structure development is proposed. The multidimensional input–output index system was augmented with a carbon emission constraint. Additionally, two classical data envelopment analysis models were integrated to establish a dynamic measurement model for energy utilization efficiency, ensuring comparability among all decision-making units. From two perspectives of industrial structure, rational degree and advanced degree, the industrial structure development index was proposed to quantitatively characterize the level of regional industrial structure development. Drawing upon the Tapio decoupling theory, an elaborate model for identifying harmonious relationships was constructed to refine the recognition of the harmonious state between energy utilization efficiency and industrial structural development. A city-scale case study was conducted in Heilongjiang Province, a typical energy province in Northern China. The results revealed that: (a) energy utilization efficiency in various cities has exhibited a consistent upward trend, with the average efficiency rising from 0.54 in 2010 to 0.88 in 2020. Core cities like Daqing and Harbin stand out in energy utilization, and the disparity in energy utilization levels between different cities is progressively diminishing; (b) the overall level of industrial structural development has shown a weak downward trend. Harbin has the best industrial structure development level, with a quantitative index higher than 0.8. For some cities with relatively backward industrial structures, it is necessary to clarify new industrial development positioning and promote deep optimization of industrial structures; and (c) the harmonious relationship between energy utilization efficiency and industrial structural development demonstrates stage characteristics, indicating an overall negative decoupling relationship with limited dynamic coordination. These distinct findings will assist in identifying potential solutions for achieving high-quality development in traditional industrial cities under carbon emission constraints.

Industrial structure, high-quality development of logistics industry and the economy.

The logistics industry is closely related to the high-quality economic development. At different levels of industrial structure, the relationship between high-quality development of the logistics industry and the high-quality economic development will vary, resulting in different roles and paths in promoting economic development. However, there is still a lack of research on the relationship between high-quality development of the logistics industry and high-quality economic development at different levels of industrial structure, and further empirical research is needed. It used the benchmark regression model to analyze the impact of the high-quality development of the logistics industry on high-quality economic development, and the panel threshold model was used to analyze the impact of the logistics industry on high-quality economic development at different levels of industrial structure development. The results show that the high-quality development of the logistics industry has a positive role in promoting the high-quality economic development, and in different levels of industrial structure development, the impact of high-quality development level of logistics industry on the high-quality economic development is different. Therefore, it is necessary to further optimize the industrial structure, promote the deep integration and development of logistics and related industries, and continue to promote the high-quality development of the logistics industry. And when formulating development strategies for the logistics industry, governments and enterprises need to consider factors such as changes in industrial structure, the overall goals of national economy, people's livelihood, and social development, in order to provide solid support for achieving high-quality economic development. This paper demonstrates the importance of high-quality development of the logistics industry in high-quality economic development, and it encourages the adoption of different strategies at different stages of industrial structure development to promote high-quality development of the logistics industry, and achieve high-quality economic development.

Urban development land price distortion and industrial structure evolution in China

Urban development land price distortion and industrial structure evolution in China

WITHDRAWN: The Impact of Industrial Structure Evolution on Fiscal Revenue in Shenzhen China

Adjustment, optimization and upgrading of industrial structure is one of the important indicators that affect local fiscal revenue. To explore the relationship between industrial structure and local fiscal revenue is the basis for industrial policy formulation and fiscal expenditure arrangement and an important issue in the field of structural economics. This paper aims at exploring the inherent regularity public fiscal revenue and the upgrading of industrial structure in the process of urban economic development. We utilize data from 1996 to 2020 in the “Shenzhen Statistical Yearbook” and employ Bayesian structure time series (BSTS) model to analyze the effect of industrial structure evolution on fiscal revenue in Shenzhen. The tax revenue data is used to represent Shenzhen's fiscal revenue and the ratio of the tertiary to secondary industry added values is used to represent industrial structure evolution index. Our findings demonstrate that the impact of Shenzhen's industrial structure evolution on fiscal revenue shows a steady and positive trend from 2000 to 2004. Then it significantly increases to a peak in 2006 and goes downward. After 2017, the evolution of Shenzhen's industrial structure has negative impact on the overall fiscal revenue. Based on the results, this paper puts forward relevant policy implications for other cities in China to promote the transformation and upgrading of industrial structures.

Research on the Development of Industrial Structure in Zhejiang, China

Research on the Development of Industrial Structure in Zhejiang, China

Adaptability analysis of water pollution and advanced industrial structure in Jiangsu Province, China

The advanced development of industrial structure is the inevitable way to alleviate a regional water quality crisis. However, the adaptability between water pollution and advanced industrial structure (AIS) remains unrevealed. Analyzing the adaptability between the two can provide important enlightenment for regional differentiated policy making. Taking Jiangsu Province as a case study, this study firstly assessed the status of water pollution during the years 2013–2019 through quantitatively analyzing the grey water footprint (GWF) and grey water footprint intensity (GWFI). Secondly, the level of AIS was measured to identify the characteristics and evolution of the industrial structure. Finally, the Tapio decoupling elasticity coefficient was introduced to reflect the adaptability between GWF and AIS, and between GWFI and AIS. The main results showed that: (1) From 2013 to 2019, the GWF in Jiangsu Province showed a fluctuating decline, with an overall decrease of 27%, while the GWFI continuously declined. Agriculture was the largest sector of GWF in Jiangsu Province from 2003 to 2016, and domesticity replaced it as the largest water pollution source from 2017 to 2019. (2) The overall industrial structure of Jiangsu Province achieved a certain degree of advanced development. However, the level of AIS in Jiangsu Province was not significantly improved, and the secondary industry was still in a leading position. (3) In terms of the total amount and intensity, water pollution in Jiangsu Province was well adapted to the AIS. Among them, the strong decoupling adaptation (SDA), ideal adaptation state, was achieved between the GWF and the AIS in 75% of the year, while there has always been SDA between the GWFI and the AIS in Jiangsu Province. Therefore, targeted policies based on industrial optimization should be rationally formulated aimed at achieving effective water pollution control. The findings of adaptability analysis can be applied to regional zoning management and is conducive to promoting sustainable support of the water environment for industrial development.

Market Segmentation and Green Development Performance: Evidence from Chinese Cities.

This study is based on 2006-2019 panel data from 282 Chinese cities. Market segmentation and green development performance are empirically investigated to examine their non-linear relationship using static panel, dynamic panel, and dynamic spatial panel models. The results reveal the following: (1) Green development performance is found to have a high degree of temporal and spatial path dependence, exhibiting spatial linkage between cities. (2) Market segmentation stemming from local government protection has a clear inverted U-shaped structure in relationship with the green development performance. (3) Our analysis suggests that the upgrading of industrial structures significantly enhances green development, while factor price distortion inhibits it. The relationship between market segmentation and industrial structure upgrading is also an inverted U-shape. (4) The analysis further reveals that market segmentation has an inverted U-shaped correlation with the green development performance in western, central, and eastern cities. However, the different rates of development of industrial structures within the three regions result in varying degrees of market segmentation according to inflection point values. Moreover, aligned with the theoretical hypothesis of "resource curse," in resource-based cities (exclusively), market segmentation still affects the green development performance with a significant inverted U-shaped structure.

Green Investment, Technological Progress, and Green Industrial Development: Implications for Sustainable Development

Environmental reformation of old-fashioned sectors and the establishment of new pro-ecological businesses via green investment are the main driving forces behind the revolution in the Chinese industrial sector. Green investment aids in the growth of environmentally friendly industries. Hence, the primary objective of the analysis is to investigate the impact of green investment and technological progress on green industrial development. The results of the unit root tests encourage us to apply the ARDL model. The short and long-run estimates attached to R&D expenditures are positively significant, confirming that increasing R&D expenditures help improve the industrial structure. Similarly, the short and long-run estimates attached to green finance investment are positively significant, signifying that green investment benefits the industrial structure. Empirical findings show that technology significantly aggravates industrial structure development in only the long run. Thus, for green industrial development in China, there is a need to increase green investment and technological development up to top-level design.